def e_016():
a = ProjectVariable()
a.experiment_name = '016. caviar: selu + alphadropout=0.1'
a.ranking_number = 36
a.iterations = 10
a.activation_function = 'selu'
a.datasets = ['caviar']
a.log_file = 'thesis_experiment_log.txt'
a.dropout_rate = 0.1
scn.super_main(a)
def e_077():
a = ProjectVariable()
a.experiment_name = '077. prid450: selu + alphadropout=0.1'
a.ranking_number = 100
a.iterations = 30
a.activation_function = 'selu'
a.datasets = ['prid450']
a.log_file = 'thesis_experiment_log.txt'
a.dropout_rate = 0.1
scn.super_main(a)
def e_066():
a = ProjectVariable()
a.experiment_name = '066. grid: selu + alphadropout=0.05 + batchnorm'
a.ranking_number = 100
a.iterations = 10
a.activation_function = 'selu'
a.datasets = ['grid']
a.log_file = 'thesis_experiment_log.txt'
a.dropout_rate = 0.05
scn.super_main(a)
def e_079():
a = ProjectVariable()
a.experiment_name = '079. prid450: selu + alphadropout=0.05 + no batchnorm'
a.ranking_number = 100
a.iterations = 30
a.activation_function = 'selu'
a.datasets = ['prid450']
a.log_file = 'thesis_experiment_log.txt'
a.head_type = 'simple'
a.dropout_rate = 0.05
scn.super_main(a)
def e_057():
a = ProjectVariable()
a.experiment_name = '057. viper: selu + alphadropout=0.1 + no batchnorm'
a.ranking_number = 100
a.iterations = 10
a.activation_function = 'selu'
a.datasets = ['viper']
a.log_file = 'thesis_experiment_log.txt'
a.head_type = 'simple'
a.dropout_rate = 0.1
scn.super_main(a)
def e_074():
a = ProjectVariable()
a.experiment_name = '074. pretend save viper for priming'
a.epochs = 100
# a.save_inbetween = True
# a.name_indication = 'dataset_name'
# a.save_points = [100]
a.ranking_number = 316
a.iterations = 1
a.activation_function = 'elu'
a.neural_distance = 'absolute'
a.datasets = ['viper']
a.log_file = 'thesis_experiment_log.txt'
scn.super_main(a)
def e_034():
a = ProjectVariable()
a.experiment_name = '034. cnn_lstm on prid2011, AD=0.1'
a.epochs = 100
a.iterations = 1
a.batch_size = 32
a.activation_function = 'selu'
a.datasets = ['prid2011']
a.video_head_type = 'cnn_lstm'
a.sequence_length = 20
a.ranking_number = 30
a.dropout_rate = 0.1
a.lstm_units = 64
srcn.super_main(a)
def e_032():
a = ProjectVariable()
a.experiment_name = '032. 3D convolutions on prid2011'
a.epochs = 100
a.iterations = 1
a.batch_size = 32
a.activation_function = 'elu'
a.datasets = ['prid2011']
a.video_head_type = '3d_convolution'
a.sequence_length = 20
a.kernel = (3, 3, 3)
a.pooling_size = [[1, 4, 2], [1, 2, 2]]
a.ranking_number = 30
srcn.super_main(a)
def e_039():
a = ProjectVariable()
a.experiment_name = '039. save cuhk02 for priming'
a.epochs = 100
a.save_inbetween = True
a.name_indication = 'dataset_name'
a.save_points = [100]
a.ranking_number = 100
a.iterations = 1
a.batch_size = 32
a.activation_function = 'elu'
a.cl_min = 0.00005
a.cl_max = 0.001
a.neural_distance = 'absolute'
a.datasets = ['cuhk02']
a.log_file = 'thesis_experiment_log.txt'
scn.super_main(a)
def e_092():
a = ProjectVariable()
a.experiment_name = '092. viper > grid'
a.epochs = 100
# a.save_inbetween = True
# a.name_indication = 'dataset_name'
# a.save_points = [100]
a.ranking_number = 125
a.iterations = 10
a.batch_size = 32
a.load_weights_name = 'viper_weigths_base.h5'
a.activation_function = 'elu'
a.cl_min = 0.00005
a.cl_max = 0.001
a.neural_distance = 'absolute'
a.datasets = ['grid']
a.log_file = 'thesis_experiment_log.txt'
scn.super_main(a)
